3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 3 cited
DebUnc: Improving Large Language Model Agent Communication With Uncertainty Metrics
Luke Yoffe, Alfonso Amayuelas, William Yang Wang
Multi-agent debates have been introduced to improve the accuracy of Large Language Models (LLMs) by having multiple agents discuss solutions to a problem over several rounds of deb…
cs.CL2022★ 1 cited
An Exploration of Data Efficiency in Intra-Dataset Task Transfer for Dialog Understanding
Josiah Ross, Luke Yoffe, Alon Albalak +1
Transfer learning is an exciting area of Natural Language Processing that has the potential to both improve model performance and increase data efficiency. This study explores the…
cs.CL2022
FETA: A Benchmark for Few-Sample Task Transfer in Open-Domain Dialogue
Alon Albalak, Yi-Lin Tuan, Pegah Jandaghi +6
Task transfer, transferring knowledge contained in related tasks, holds the promise of reducing the quantity of labeled data required to fine-tune language models. Dialogue underst…